The diagnostic stage of early detection of breast cancer is currently far from perfect. With the current clinical imaging technology used for diagnostic work-up of suspicious lesions detected at breast cancer screening, approximately one out of six breast cancers are missed. This is in addition to the one out of six breast cancers already missed at the breast cancer screening stage. In addition, the rate of false positive diagnostic work-ups results in more than two out of three biopsies yielding a negative result. Clearly there is room for improvement in this very important clinical diagnostic procedure. Of the many novel imaging technologies being developed for breast cancer imaging, dedicated breast computed tomography (BCT) is one of very few that results in a true tomographic image of the breast with high contrast resolution and does not require the injection of a contrast agent or radiopharmaceutical. This makes it ideal for use as the frontline imaging technology for working up suspicious lesions detected during breast cancer screening or during clinical breast examination. In this project we propose to perform a prospective clinical trial to compare the accuracy of BCT to the current standard imaging technologies for diagnosis of breast cancer in patients with a suspicious lesion identified during breast cancer screening. To maximize the image quality of BCT we will apply to the BCT novel algorithms we have developed that result in more accurate, higher quality images with true quantitative characteristics. These algorithms involve the correction of the acquired BCT projections due to the presence of x-ray scatter, and a novel reconstruction algorithm that correctly represents the image acquisition process as one involving a spectrum of x-ray energy, rather than mono-energetic x-rays. Successful completion of this project will help introduce BCT to the clinical realm by characterizing its true potential or impact in the breast cancer diagnosis stage, where we expect it will result in fewer missed breast cancers and negative biopsies.